Backend Engineer, Applied AI

Citizen•New York, NY

3d•Onsite

About The Position

Citizen is the #1 safety app in the U.S. Every day, thousands of videos are captured live at the scene of real incidents and distributed in real time to people in every major American city. No other consumer product has this. It is a live network, a newsroom, and a safety tool at once, and it is growing again. Underneath it is a real-time system: ingest from 911 radio, CAD feeds, user video, and partner feeds; detection, verification, and geolocation; distribution to millions of devices in seconds; the live video infrastructure that carries the scene to the app; and the enterprise products and API that deliver the same intelligence to cities, hospitals, campuses, and private security. You will own core pieces of that system and ship them with a small team of engineers, human and agent. You will also build for the people inside Citizen who run the city. Our Mission Control and real-time operations team lives in ProtectOS and Regulator, our internal operating tools, all day. A meaningful share of backend work is tooling for them, and they are the most demanding users you will have. Citizen is being rebuilt as an AI-native company, and the backend is where most of the rebuild happens. AI now sits in the pipeline itself, detecting and verifying incidents and deciding what people see, and the system has to get faster, more accurate, and cheaper per incident while it does. The enterprise business is working and needs to scale on the same platform. That is a very large amount of interesting work for a very small number of people who use agents to carry it.

Requirements

Exceptional at the craft of backend engineering.
Runs agents like a second pair of hands.
Treats a wrong alert as a bug with consequences.
Distributed systems judgment, taste in code, and the instinct to know where a real-time system will break before it does.
Fluent in Go.
Comfortable in Python for the ML and data pipelines.
At home on Kubernetes and a modern cloud stack: message queues, relational and analytical stores, observability.
Carried a pager for a system people depended on.
Put ML models or LLMs into a production path and know the difference between a demo and a system with evaluation, fallbacks, and audit.
Build with AI already.
Replaced whole parts of your own workflow with agents.
Have opinions about where agents fail, and are paying attention to what is next.
Measure: instrument before you argue, and know the difference between an event that fired and an event that landed in the warehouse.
High agency: handed a direction, come back with a better one.
Want to drive, not only build.
Care about the mission.
Want to be in New York, in the office, every day.

Nice To Haves

Worked on live video or streaming infrastructure, or want to and can show you learn systems like it fast.

Responsibilities

Own core pieces of the real-time system and ship them with a small team of engineers, human and agent.
Build tooling for the Mission Control and real-time operations team.
Own and ship new ideas and new services where they move the company's growth and current focus.
Register Segment events with the data team, check them in BigQuery, and ensure the numbers leadership sees are the numbers the system produced.
Extend and operate agent loops that draft, review, test, and operate backend code.
Propose where agents run alone.
Work daily with iOS and Android on the contracts, with ML on the models, with Data on events, and with Mission Control as your primary internal user.
Ship to production in week one.
Join the on-call rotation as a shadow.
Identify the three things that will break first and start on the first.
Drive your first initiative end to end.
Land one measurable improvement in latency, correctness, or cost.
Take your first solo on-call week.
Extend the agent loops already wired into the backend repo and propose the first one to run without a human, in test generation, review, or on-call triage.
Ship the first AI-in-pipeline capability, video improvement, or enterprise service to real users.
Present the roadmap for the systems you own, with the numbers behind it.